Method, apparatus, and medium for evaluating the lifetime of a dc bus capacitor

Abstract

The application discloses a life evaluation method, device, equipment and medium of a direct-current bus capacitor, and relates to the technical field of capacitor detection. The life evaluation method comprises the following steps: establishing a simulation model of a motor driving system based on a typical driving cycle of a target electric vehicle, and obtaining a ripple current time sequence of the direct-current bus capacitor in the whole driving cycle. A second-order RC thermal network model of the capacitor is established through finite element thermal simulation fitting, and the ripple current time sequence data is converted into a capacitor hot spot temperature time sequence. Based on a linear cumulative damage theory, the cumulative damage amount of the capacitor under the hot spot temperature time sequence is calculated. An aging feedback mechanism is introduced in the damage accumulation process to update the equivalent series resistance value of the capacitor in real time. A Monte Carlo method is adopted to simulate the manufacturing tolerance of the capacitor through random sampling, a large number of samples are generated and life calculation is performed, and finally, a Weibull distribution is adopted to fit the life data to obtain the reliability index of the capacitor.

Description

Technical Field

[0001] This invention relates to the field of capacitance testing technology, and more specifically, to a method, apparatus, equipment, and dielectric for assessing the lifespan of a DC bus capacitor. Background Technology

[0002] Metallized polypropylene film capacitors are commonly used in the DC link of motor control systems in new energy electric vehicles to suppress high-frequency harmonic currents generated by power switching devices and smooth DC bus voltage. They are key components in electric drive systems to ensure voltage stability and operational safety.

[0003] These capacitors withstand drastically changing ripple currents under different operating conditions such as vehicle acceleration, constant speed, and deceleration. They operate continuously in the high-temperature and heat-limited environment of the inverter compartment, and their internal power loss and hot spot temperature fluctuate strongly over time. If the reliability assessment and life prediction are inaccurate, it will directly threaten the stability and safety of the entire vehicle's electric drive system.

[0004] In existing technologies, reliability assessments of thin-film capacitors often employ experimental or computational methods under fixed stress conditions. These typically involve accelerated life testing or life model analysis based on constant ripple current and isothermal environments. The assessment approach and parameter selection are relatively static, making it difficult to reflect the dynamic thermo-electric stress characteristics that change over time under typical driving cycles. Furthermore, traditional assessment methods often treat the equivalent series resistance as a constant parameter, neglecting the positive feedback process of increased losses and temperature rise caused by the gradual increase in equivalent series resistance during capacitor aging. This leads to overly optimistic life estimates under high-stress, long-life conditions, making it difficult to provide accurate data for the structural design and component selection of electric drive systems.

[0005] Furthermore, existing assessment methods often focus on estimating the lifespan of a single capacitor under nominal conditions, failing to adequately consider the lifespan dispersion caused by factors such as manufacturing tolerances and environmental fluctuations. In engineering contexts where multiple capacitors are typically connected in series and parallel to form capacitor banks on DC buses, there is a lack of reliability analysis and quantitative indicators for capacitor banks as a whole. It is difficult to provide reliability parameters such as B10 lifespan from a statistical perspective, and thus cannot effectively support predictive maintenance strategies and replacement cycle formulation for capacitors. Summary of the Invention

[0006] The present invention provides a method, apparatus, device and dielectric for assessing the lifespan of a DC bus capacitor, in order to improve at least one of the above-mentioned technical problems.

[0007] In a first aspect, the present invention provides a method for evaluating the lifespan of a DC bus capacitor, comprising steps S1 to S4.

[0008] S1. Based on the typical driving cycle of the target electric vehicle, establish a simulation model of the motor drive system and obtain the ripple current time series of the DC bus capacitor throughout the entire driving cycle.

[0009] S2. By fitting the finite element thermal simulation, a second-order RC thermal network model of the capacitor is established, and the ripple current time series data is converted into a capacitor hot spot temperature time series.

[0010] S3. Based on the linear cumulative damage theory, calculate the cumulative damage of the capacitor under the hot spot temperature time series. An aging feedback mechanism is introduced during the damage accumulation process to update the equivalent series resistance value of the capacitor in real time.

[0011] S4. Using the Monte Carlo method, the manufacturing tolerance of the capacitor is simulated by random sampling, a large number of samples are generated and the lifespan is calculated. Finally, the Weibull distribution is used to fit the lifespan data to obtain the reliability index of the capacitor.

[0012] As a further aspect of the present invention, S1 specifically includes: building a simulation model of the electric drive system in MATLAB and / or Simulink based on a typical driving cycle of the target electric vehicle. Then, the model is run to collect the ripple current time series within a complete typical driving cycle.

[0013] As a further aspect of the present invention, the electric drive system simulation model includes the following sub-modules:

[0014] Driving Cycle Module: Imports standard speed-time curves for typical driving cycles.

[0015] Vehicle dynamics model: Calculate the required torque using the vehicle's driving equations. .

[0016] .

[0017] In the formula For the torque acting on the wheel axle, For gear ratio, For driving force, For the effective radius of the wheel, For rolling resistance coefficient, For the quality of the whole vehicle, For gravitational acceleration, air density For speed, For the vehicle's frontal area, For air drag coefficient, For time, It represents the differential.

[0018] Motor and control model: A permanent magnet synchronous motor model with maximum torque-to-current ratio control is adopted, combined with space vector pulse width modulation to drive a three-phase inverter, realizing the conversion from target torque to inverter switching signal.

[0019] Battery and DC bus model: The battery DC bus voltage is set to the rated value, and the DC bus is used to reproduce the multi-capacitor parallel configuration of the real vehicle.

[0020] As a further aspect of the present invention, the typical driving cycle is the ECE-15 city driving cycle, used to simulate frequent start-stop, acceleration, and deceleration conditions in urban environments. A complete ECE-15 city driving cycle lasts 195 seconds. Ripple current time series. The sampling interval is 1 second.

[0021] As a further embodiment of the present invention, the second-order RC thermal network model is the Foster thermal network model.

[0022] As a further aspect of the present invention, step S2 specifically includes:

[0023] A three-dimensional model of the capacitor was established using finite element method software. A step power excitation was applied to the model, and transient thermal simulation was performed to obtain the temperature rise curve of the capacitor's hot spot. .

[0024] By fitting its transient thermal impedance curve Extract the parameters of the second-order Foster thermal network.

[0025] .

[0026] .

[0027] .

[0028] In the formula The first thermal resistance of the Foster thermal network, For the second thermal resistance of the Foster thermal network, The first thermal time constant, The second thermal time constant, For the first heat capacity of the Foster thermal network, For the second heat capacity of the Foster thermal network, For the natural base, For time.

[0029] Calculate the power loss at each moment. : In the formula For ripple current time series, for Equivalent series resistance at any time.

[0030] Power loss sequence Input a second-order Foster thermal network and use the recursive property to calculate the hot spot temperature second by second. Obtain hotspot temperature time series .

[0031] .

[0032] In the formula For the first capacitor hot spot temperature per second For time series numbering, For the first Capacitor power loss per second For the serial number in the Foster thermal network, For the Foster thermal network thermal resistance, For the first A thermal time constant, The ambient temperature.

[0033] As a further aspect of the present invention, based on the linear cumulative damage theory, the cumulative damage of the capacitor under the hot spot temperature time series is calculated, specifically as follows:

[0034] Hotspot temperature time series The cumulative operating time within different temperature ranges during a driving cycle was statistically analyzed. The predicted lifespan at each temperature was calculated using an Arrhenius-modified lifespan model. Then, the damage for one driving cycle was calculated. .

[0035] .

[0036] .

[0037] In the formula For temperature Predicted lifespan Reference temperature Rated life under the following conditions For the first Actual operating temperature in each temperature range For the first The cumulative working time for each temperature range.

[0038] As a further aspect of the present invention, the aging feedback mechanism is as follows: when the accumulated damage reaches a set threshold, the equivalent series resistance value of the capacitor is updated according to a predetermined functional relationship based on the current total damage, and the power loss and hot spot temperature distribution are recalculated.

[0039] The aging feedback mechanism specifically includes:

[0040] Set damage accumulation threshold Initialize total damage Each completed One cycle Increase Damage for one driving cycle.

[0041] when Da When the value is an integer multiple, update the equivalent series resistance. The equivalent series resistance update model is as follows:

[0042] .

[0043] In the formula For damage-based Updated equivalent series resistance For the initial equivalent series resistance, For the first fitting parameters, is the second fitting parameter.

[0044] The updated equivalent series resistance is fed back to S2, and the losses and temperatures of subsequent cycles are recalculated, forming a dynamic closed loop of damage accumulation - parameter update - thermoelectric correction - damage recalculation. This process is repeated until... Determine failure and record the predicted lifetime at this point. .

[0045] As a further aspect of the present invention, step S4 specifically includes:

[0046] Assuming initial equivalent series resistance Following a normal distribution, a predetermined number of initial equivalent series resistances are generated. Random sample.

[0047] For each sample Perform steps S1 to S3 to calculate the corresponding lifetime value. This forms a lifetime distribution dataset.

[0048] The dataset is fitted using a two-parameter Weibull distribution, and its cumulative distribution function is: In the formula, For reliability function, For the natural base, For time, For scale parameters, For shape parameters.

[0049] Extract key reliability metrics. Among these, the reliability metrics include B10 lifetime, which is the time when 90% of the capacitor samples can still function normally. In the formula Lifetime is B10.

[0050] Capacitor bank reliability assessment. The lifespan of the capacitor bank was calculated using the Weibull distribution function.

[0051] .

[0052] In the formula For the overall reliability of the capacitor bank, , … These are the 1st, 2nd... capacitors in the capacitor bank, respectively. The reliability of each capacitor.

[0053] Secondly, the present invention provides a life assessment device for a DC bus capacitor, which includes a current acquisition module, a temperature acquisition module, a damage accumulation module, and an index module.

[0054] The current acquisition module is used to establish a simulation model of the motor drive system based on the typical driving cycle of the target electric vehicle, and to acquire the ripple current time series of the DC bus capacitor throughout the entire driving cycle.

[0055] The temperature acquisition module is used to establish a second-order RC thermal network model of the capacitor through finite element thermal simulation fitting, and to convert the ripple current time series data into a capacitor hot spot temperature time series.

[0056] The damage accumulation module is used to calculate the cumulative damage of the capacitor over the hot spot temperature time series based on linear cumulative damage theory. An aging feedback mechanism is introduced during the damage accumulation process to update the equivalent series resistance value of the capacitor in real time.

[0057] The index module is used to simulate capacitor manufacturing tolerances through random sampling using the Monte Carlo method, generate a large number of samples and perform lifetime calculations, and finally fit the lifetime data using the Weibull distribution to obtain the reliability index of the capacitor.

[0058] Thirdly, the present invention provides a life assessment device for a DC bus capacitor, comprising a processor, a memory, and a computer program stored in the memory. The computer program can be executed by the processor to implement a life assessment method for a DC bus capacitor as described in any paragraph of the first aspect.

[0059] Fourthly, the present invention provides a computer-readable storage medium. The computer-readable storage medium includes a stored computer program, wherein, when the computer program is executed, it controls the device containing the computer-readable storage medium to perform a method for assessing the lifespan of a DC bus capacitor as described in any paragraph of the first aspect.

[0060] By adopting the above technical solution, the present invention can achieve the following technical effects:

[0061] This invention presents a method for assessing the lifespan of DC bus capacitors. It constructs a comprehensive assessment system integrating dynamic task profiles, an electro-thermal coupling model, a damage accumulation algorithm with aging feedback, and Monte Carlo reliability simulation. This method successfully addresses three major limitations of traditional methods in the reliability assessment of thin-film capacitors for electric vehicles: First, it achieves a leap from static stress analysis to dynamic operating condition simulation, making the assessment conditions more realistic. Second, by introducing a feedback mechanism that reflects the change in equivalent series resistance with damage, it accurately captures the positive feedback effect during the aging process, avoiding overly optimistic predictions. Third, by employing a reliability index based on statistical distribution (the lifespan of the B10 capacitor bank), it provides a quantitative and scientific basis for predictive health management and replacement strategies for capacitors, significantly improving the reliability design and maintenance level of electric drive systems. Attached Figure Description

[0062] To more clearly illustrate the technical solution of the present invention, the accompanying drawings used in the specific embodiments of the present invention will be briefly introduced below. It should be understood that the following drawings only show some specific embodiments of the present invention and should not be regarded as a limitation on the scope. For those skilled in the art, other related drawings can be obtained from these drawings without creative effort.

[0063] Figure 1 This is a general flowchart of the reliability assessment method provided in the embodiments of the present invention.

[0064] Figure 2 This is the life assessment process for metallized film capacitors used in electric vehicles.

[0065] Figure 3 The failure probability density distribution and reliability changes of capacitors.

[0066] Figure 4 The speed-time curve for the ECE-15 driving cycle. Detailed Implementation

[0067] The technical solutions of the present invention will now be clearly and completely described with reference to the accompanying drawings in the embodiments of the present invention.

[0068] Example 1, please refer to Figures 1 to 2The first embodiment of the present invention provides a method for assessing the lifespan of a DC bus capacitor. This method can be performed by a DC bus capacitor lifespan assessment device (hereinafter referred to as: lifespan assessment device). Specifically, it is performed by one or more processors within the lifespan assessment device to implement steps S1 to S4.

[0069] The following section uses a 110μF metallized polypropylene film capacitor used in the DC bus of a certain type of electric vehicle motor control system as an example to describe in detail the life assessment method of the DC bus capacitor of the present invention, and to assess its life and reliability under urban driving conditions.

[0070] S1. Based on the typical driving cycle of the target electric vehicle, establish a simulation model of the motor drive system and obtain the ripple current time series of the DC bus capacitor throughout the entire driving cycle.

[0071] This step aims to obtain the dynamic current load sequence of the capacitor under actual operation. Specifically, based on the typical driving cycle of the target electric vehicle, a simulation model of the electric drive system is built in MATLAB and / or Simulink. Then, the model is run to collect the ripple current time series within a complete typical driving cycle, which serves as the dynamic task profile for subsequent evaluation.

[0072] The typical driving cycle is the ECE-15 city driving cycle, used to simulate frequent start-stop, acceleration, and deceleration conditions in urban environments. A complete ECE-15 city driving cycle lasts 195 seconds. Ripple current time series. The sampling interval is 1 second. ECE-15 is a standard urban driving cycle used to evaluate the driving range of family vehicles.

[0073] The electric drive system simulation model includes the following sub-modules:

[0074] 1. Driving Cycle Module: Imports the standard speed-time curve for the ECE-15 city driving cycle. The maximum speed is 50 km / h, the average speed is approximately 19 km / h, the duration of one cycle is 195 seconds, and the distance traveled is 0.9941 km. The speed-time curve for the ECE-15 driving cycle is shown below. Figure 4 As shown.

[0075] By building the corresponding model in Simulink, the current curve of the capacitor during vehicle operation can be obtained.

[0076] 2. Vehicle dynamics model: Calculate the required torque using the vehicle's driving equations. .

[0077] .

[0078] In the formula For the torque acting on the wheel axle, For gear ratio, For driving force, For the effective radius of the wheel, For rolling resistance coefficient, For the quality of the whole vehicle, For gravitational acceleration, air density For speed, For the vehicle's frontal area, For air drag coefficient, For time, It represents the differential.

[0079] in, Units: The unit is m / s. Units: .

[0080] By building the corresponding model in Simulink, the current curve of the capacitor during vehicle operation can be obtained.

[0081] 3. Motor and Control Model: A permanent magnet synchronous motor (PMSM) model controlled by maximum torque-to-current ratio (MTPA) is used, combined with space vector pulse width modulation (SVPWM, switching frequency 10kHz) to drive a three-phase inverter, realizing the conversion from target torque to inverter switching signals. Simulations output the ripple current of the DC bus capacitor during a complete driving cycle (195 seconds). Time series data.

[0082] 4. Battery and DC-Link Model: The battery DC bus voltage is set to its rated value. The DC-Link is used to replicate the multi-capacitor parallel configuration of the actual vehicle. The DC-Link is the DC bus connecting the battery (DC source) and the inverter (AC source), and its main function is as an "energy buffer" or "filter." By running the model, the ripple current time series is collected over a complete ECE-15 cycle (195 seconds). (Sampling interval 1 second), this sequence is a dynamic task profile for subsequent evaluation.

[0083] S2. By fitting the finite element thermal simulation, a second-order RC thermal network model of the capacitor is established, and the ripple current time series data is converted into a capacitor hot spot temperature time series.

[0084] Step S2 is used to convert the ripple current into a temperature profile of the hot spot inside the capacitor. Preferably, step S2 specifically includes steps S21 to S24. Steps S21 to S22 are used to obtain the dynamic thermal response parameters of the capacitor. Then, the power loss at each moment is calculated. Finally, the hot spot temperature is calculated second by second using a recursive characteristic.

[0085] The second-order RC thermal network model is the Foster thermal network model. The core of the Foster model is to fit the transient thermal impedance curve of the device by combining multiple "thermal resistance-thermal capacity (RC) units" in series and parallel. Its thermal resistance and thermal capacity parameters are obtained by fitting the results of finite element thermal simulation.

[0086] S21. Establish a three-dimensional model of the capacitor using finite element software (such as COMSOL), apply a step power excitation to it, perform transient thermal simulation, and obtain the temperature rise curve of the capacitor's hot spot temperature. .

[0087] S22, By fitting its transient thermal resistance curve Extract the parameters of the second-order Foster thermal network.

[0088] The fitting formula is:

[0089] .

[0090] .

[0091] .

[0092] In the formula The first thermal resistance of the Foster thermal network, For the second thermal resistance of the Foster thermal network, The first thermal time constant, The second thermal time constant, For the first heat capacity of the Foster thermal network, For the second heat capacity of the Foster thermal network, For the natural base, For time.

[0093] In a preferred embodiment, a set of parameters is obtained through fitting:

[0094] .

[0095] .

[0096] .

[0097] .

[0098] S23. Calculate the power loss at each moment. :

[0099] .

[0100] In the formula For ripple current time series, for Equivalent series resistance at any time.

[0101] initial value Take the nominal value from the product manual.

[0102] S24, Power loss sequence Input a second-order Foster thermal network and use the recursive property to calculate the hot spot temperature second by second. Obtain hotspot temperature time series .

[0103] The recursive formula is:

[0104] .

[0105] In the formula For the first capacitor hot spot temperature per second For time series numbering, For the first Capacitor power loss per second For the serial number in the Foster thermal network, For the Foster thermal network thermal resistance, For the first A thermal time constant, The ambient temperature.

[0106] Preferably, ambient temperature Set the inverter compartment temperature to, for example, 70°C.

[0107] S3. Based on the linear cumulative damage theory, calculate the cumulative damage of the capacitor under the hot spot temperature time series. An aging feedback mechanism is introduced during the damage accumulation process to update the equivalent series resistance value of the capacitor in real time.

[0108] This step is based on the linear cumulative damage theory and introduces an aging feedback mechanism.

[0109] Based on the linear cumulative damage theory, the cumulative damage of the capacitor under the hot spot temperature time series is calculated as follows:

[0110] Hotspot temperature time series The cumulative operating time within different temperature ranges during a driving cycle was statistically analyzed. The predicted lifespan at each temperature was calculated using an Arrhenius-modified lifespan model. Then, the damage for one driving cycle was calculated. .

[0111] .

[0112] .

[0113] In the formula For temperature Predicted lifespan Reference temperature Rated life under the following conditions For the first Actual operating temperature in each temperature range For the first The cumulative operating time across multiple temperature ranges. In this embodiment, Take 70℃, The time is set to 100,000 hours. In other embodiments, the time can be set according to actual parameters, and the present invention does not impose specific limitations on this.

[0114] The aging feedback mechanism is as follows: when the accumulated damage reaches a set threshold, the equivalent series resistance value of the capacitor is updated according to a predetermined functional relationship based on the current total damage, and the power loss and hot spot temperature distribution are recalculated.

[0115] The aging feedback mechanism specifically includes:

[0116] Set damage accumulation threshold Initialize total damage Each completed One cycle Increase Damage for one driving cycle.

[0117] when Da When the value is an integer multiple, update the equivalent series resistance. The equivalent series resistance update model is as follows:

[0118] .

[0119] In the formula For damage-based Updated equivalent series resistance For the initial equivalent series resistance, For the first fitting parameters, is the second fitting parameter. This is the equivalent series resistance.

[0120] Fitting parameters and Used for accelerated aging tests to reflect damage and equivalent series resistance. The correlation of growth. In this embodiment, , In other embodiments, those skilled in the art can make their own settings, and the present invention does not impose specific limitations on them.

[0121] The updated equivalent series resistance is fed back to S2, and the losses and temperatures of subsequent cycles are recalculated, forming a dynamic closed loop of damage accumulation - parameter update - thermoelectric correction - damage recalculation. This process is repeated until... Determine failure and record the predicted lifetime at this point. .

[0122] S4. Using the Monte Carlo method, the capacitor manufacturing tolerance is simulated through random sampling to generate a large number of samples and perform lifetime calculations. Finally, the lifetime data is fitted using a Weibull distribution to obtain the reliability index of the capacitor. Specifically, step S4 upgrades "deterministic prediction" to "probabilistic reliability assessment".

[0123] Specifically, considering manufacturing tolerances, assume the initial equivalent series resistance It follows a normal distribution. In this embodiment, the mean of the normal distribution is 13mΩ and the standard deviation is 0.65mΩ (5% tolerance). In other embodiments, other values ​​can be used, and this invention does not specifically limit them.

[0124] The Monte Carlo simulation is as follows:

[0125] 1. Assume the initial equivalent series resistance Following a normal distribution, a predetermined number of initial equivalent series resistances are generated. Random samples. Each sample represents a virtual capacitor; in this embodiment, the preset number is 50,000.

[0126] 2. For each sample Perform steps S1 to S3 to calculate the corresponding lifetime value. This forms a lifetime distribution dataset.

[0127] The dataset is fitted using a two-parameter Weibull distribution, and its cumulative distribution function is:

[0128] .

[0129] In the formula, For reliability function, For the natural base, For time, For scale parameters, For shape parameters.

[0130] 3. Extract key reliability indicators. These indicators include B10 lifetime, which is the time it takes for 90% of the capacitor samples to still function normally. In the industry, B10 lifetime is commonly used to represent the lifespan of a capacitor; it refers to the time it takes for 10% of the capacitor samples to fail. Specifically, B10 lifetime is used to calculate reliability. The time of day.

[0131] .

[0132] In the formula Lifetime is B10.

[0133] B10 lifespan is the core basis for "predictive maintenance". Figure 3 The failure distribution of the capacitors is shown. Introducing parameter variations, we obtain a B10 lifetime of 47675.51 hours for a single capacitor. This means that out of 50,000 samples, 90% of the capacitors will fail within 47675.51 hours.

[0134] 4. Capacitor Bank Reliability Assessment. From a reliability perspective, the DC-Link capacitor bank is a series-connected reliable system. Due to power density limitations of traction inverters, manufacturers typically do not add redundant capacitors to the circuit. This means that the failure of any capacitor in the capacitor bank will cause the entire capacitor bank to lose its reliable operating capability. Specifically, the lifetime of the capacitor bank is calculated using the Weibull distribution function.

[0135] Therefore, the reliability of the capacitor bank can be evaluated using the following formula:

[0136] .

[0137] In the formula For the overall reliability of the capacitor bank, , … These are the 1st, 2nd... capacitors in the capacitor bank, respectively. The reliability of each capacitor.

[0138] It can be seen that the B10 life of the entire capacitor bank is 38617.16 hours. Based on this result, the maintenance plan is adjusted to ensure timely replacement of capacitors before they fail, thereby minimizing the risk of failure caused by capacitor failure and maximizing the reliability and safety of the electric drive system of the electric vehicle.

[0139] This invention presents a method for assessing the lifespan of DC bus capacitors. It constructs a comprehensive assessment system integrating dynamic task profiles, an electro-thermal coupling model, a damage accumulation algorithm with aging feedback, and Monte Carlo reliability simulation. This method successfully addresses three major limitations of traditional methods in the reliability assessment of thin-film capacitors for electric vehicles: First, it achieves a leap from static stress analysis to dynamic operating condition simulation, making the assessment conditions more realistic. Second, by introducing a feedback mechanism that reflects the change in equivalent series resistance with damage, it accurately captures the positive feedback effect during the aging process, avoiding overly optimistic predictions. Third, by employing a reliability index based on statistical distribution (the lifespan of the B10 capacitor bank), it provides a quantitative and scientific basis for predictive health management and replacement strategies for capacitors, significantly improving the reliability design and maintenance level of electric drive systems.

[0140] Specifically, through a closed-loop process of "task profile acquisition - electro-thermal behavior analysis - life assessment and aging feedback - reliability assessment", it achieves accurate assessment from microscopic electro-thermal mechanisms to macroscopic population statistics, providing quantitative support for the reliability design and predictive maintenance of electric drive systems.

[0141] Example 2: The present invention provides a life assessment device for a DC bus capacitor, which includes a current acquisition module, a temperature acquisition module, a damage accumulation module, and an index module.

[0142] The current acquisition module is used to establish a simulation model of the motor drive system based on the typical driving cycle of the target electric vehicle, and to acquire the ripple current time series of the DC bus capacitor throughout the entire driving cycle.

[0143] The temperature acquisition module is used to establish a second-order RC thermal network model of the capacitor through finite element thermal simulation fitting, and to convert the ripple current time series data into a capacitor hot spot temperature time series.

[0144] The damage accumulation module is used to calculate the cumulative damage of the capacitor over the hot spot temperature time series based on linear cumulative damage theory. An aging feedback mechanism is introduced during the damage accumulation process to update the equivalent series resistance value of the capacitor in real time.

[0145] The index module is used to simulate capacitor manufacturing tolerances through random sampling using the Monte Carlo method, generate a large number of samples and perform lifetime calculations, and finally fit the lifetime data using the Weibull distribution to obtain the reliability index of the capacitor.

[0146] Example 3: This invention provides a life assessment device for a DC bus capacitor, comprising a processor, a memory, and a computer program stored in the memory. The computer program can be executed by the processor to implement a life assessment method for a DC bus capacitor as described in any paragraph of Example 1.

[0147] It is understood that the life assessment device can be an electronic device with computing power, such as a portable laptop computer, desktop computer, server, smartphone, or tablet computer.

[0148] Example 4: This invention provides a computer-readable storage medium. The computer-readable storage medium includes a stored computer program, wherein, when the computer program is executed, it controls the device containing the computer-readable storage medium to perform a method for assessing the lifespan of a DC bus capacitor as described in any paragraph of Example 1.

[0149] Obviously, the embodiments described above are only some embodiments of the present invention, and not all embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without inventive effort are within the scope of protection of the present invention.

[0150] In the several embodiments provided in this invention, it should be understood that the disclosed apparatus and methods can also be implemented in other ways. The apparatus and method embodiments described above are merely illustrative. For example, the flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of apparatus, methods, and computer program products according to various embodiments of the present invention. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks may occur in a different order than those marked in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram and / or flowchart, and combinations of blocks in block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or action, or using a combination of dedicated hardware and computer instructions.

[0151] In addition, the functional modules in the various embodiments of the present invention can be integrated together to form an independent part, or each module can exist independently, or two or more modules can be integrated to form an independent part.

[0152] If the aforementioned functions are implemented as software functional modules and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, electronic device, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory, random access memory, magnetic disks, or optical disks. It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0153] The terminology used in the embodiments of this invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. The singular forms “a,” “the,” and “the” used in the embodiments of this invention are also intended to include the plural forms unless the context clearly indicates otherwise.

[0154] It should be understood that the term "and / or" used in this article is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, and B existing alone. Additionally, the character " / " in this article generally indicates that the preceding and following related objects have an "or" relationship.

[0155] Depending on the context, the word "if" as used here can be interpreted as "when," "when," "in response to determination," or "in response to detection." Similarly, depending on the context, the phrase "if determination" or "if detection (of the stated condition or event)" can be interpreted as "when determination," "in response to determination," "when detection (of the stated condition or event)," or "in response to detection (of the stated condition or event)."

[0156] The terms "first" and "second" used in the embodiments are merely to distinguish similar objects and do not represent a specific ordering of objects. It is understood that "first" and "second" can be interchanged in a specific order or sequence where permitted. It should be understood that the objects distinguished by "first" and "second" can be interchanged where appropriate so that the embodiments described herein can be implemented in an order other than those illustrated or described herein.

[0157] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method of life assessment of a DC bus capacitor, characterized by, Comprise: S1, based on the typical driving cycle of the target electric vehicle, a simulation model of the motor drive system is established, and the ripple current time sequence of the DC bus capacitor in the entire driving cycle is obtained; S2, through finite element thermal simulation fitting, a second-order RC thermal network model of the capacitor is established, and the ripple current time sequence data is converted into capacitor hot spot temperature time sequence; S3, based on the linear cumulative damage theory, the cumulative damage of the capacitor under the hot spot temperature time sequence is calculated; an aging feedback mechanism is introduced in the damage accumulation process to update the equivalent series resistance value of the capacitor in real time; S4, using the Monte Carlo method, the manufacturing tolerance of the capacitor is simulated by random sampling, a large number of samples are generated and life calculation is performed, and finally the reliability index of the capacitor is obtained by fitting the life data with Weibull distribution; The aging feedback mechanism is: when the cumulative damage reaches a set threshold, the equivalent series resistance value of the capacitor is updated according to the predetermined function relationship according to the current total damage, and the power loss and hot spot temperature distribution are recalculated; The aging feedback mechanism specifically includes: Setting a damage accumulation threshold , initializing total damage ; increasing the total damage by ; ; damage for one driving cycle; When To The equivalent series resistance is updated when the integer multiple is reached; the equivalent series resistance update model is: ； In the formula is based on the damage the updated equivalent series resistance, is the initial equivalent series resistance, is the first fitting parameter, is the second fitting parameter; The updated equivalent series resistance is fed back to S2, and the loss and temperature of the subsequent cycle are recalculated to form a dynamic closed loop of damage accumulation-parameter update-thermoelectric correction-damage recalculation; repeat this process until determine failure, record the predicted life at this time .

2. The method for evaluating the lifetime of a DC bus capacitor according to claim 1, characterized by, Based on the typical driving cycle of the target electric vehicle, a simulation model of the motor drive system is established, and the ripple current time sequence data of the DC bus capacitor in the entire driving cycle is obtained, specifically including: Based on the typical driving cycle of the target electric vehicle, an electric drive system simulation model is built in MATLAB and / or Simulink; then the model is run to collect the ripple current time sequence in a complete typical driving cycle; The electric drive system simulation model includes the following sub-modules: Driving cycle module: import the standard speed-time curve of the typical driving cycle; Vehicle dynamics model: Demand torque is calculated by vehicle kinematics equations ; ； wherein is the torque acting on the wheel axle, is the gear ratio, is the driving force, is the effective radius of the wheel, is the rolling resistance coefficient, is the mass of the vehicle, is the gravitational acceleration, is the air density is the velocity, is the frontal area of the vehicle, is the air resistance coefficient, is the time, denotes differentiation; Motor and control model: a permanent magnet synchronous motor model with maximum torque current ratio control is used, combined with a space vector pulse width modulation drive three-phase inverter, to realize the conversion from target torque to inverter switch signal; Battery and DC bus model: the battery DC bus voltage is set to the rated value, and the DC bus is used to restore the parallel configuration of multiple capacitors in the actual vehicle.

3. A method of evaluating the lifetime of a DC bus capacitor according to claim 2, characterized in that The typical drive cycle is the ECE-15 urban drive cycle, used to simulate urban frequent start-stop, acceleration and deceleration conditions; the complete ECE-15 urban drive cycle has a duration of 195 seconds; the time series of the ripple current has a sampling interval of 1 second.

4. The method of claim 1, wherein, The second-order RC thermal network model is a Foster thermal network model; Through finite element thermal simulation fitting, a second-order RC thermal network model of the capacitor is established, and the ripple current time sequence data is converted into capacitor hot spot temperature time sequence data, specifically including: A three-dimensional model of the capacitor is established by finite element software, a first step power excitation is applied to it, transient thermal simulation is carried out, and the temperature rising curve of the capacitor hot spot temperature is obtained ; By fitting its transient thermal impedance curve the second order Foster thermal network parameters are extracted; ； ； ； wherein is a first thermal resistance of the Foster thermal network, is a second thermal resistance of the Foster thermal network, is a first thermal time constant, is a second thermal time constant, is a first thermal capacitance of the Foster thermal network, is a second thermal capacitance of the Foster thermal network, is a natural base, is time; calculating the power loss at each time instant : ; where is the ripple current time series, is the equivalent series resistance at the time instant a sequence of power losses inputting a second order foster thermal network, calculating hotspot temperature second by second using recursive property , obtaining a time series of hotspot temperature ; ； wherein is the number of the second capacitor hotspot temperature, is the number of the time series, is the number of the second capacitor power loss, is the number of the order in the Foster thermal network, is the number of the thermal resistance of the Foster thermal network, is the number of the thermal time constant, is the ambient temperature.

5. The method of claim 1, wherein, Based on the linear cumulative damage theory, the cumulative damage amount of the capacitor under the hotspot temperature time sequence is calculated, specifically: the hotspot temperature time sequence is divided into a plurality of temperature intervals, and the cumulative working time of each temperature interval in a driving cycle is counted The cumulative working time of different temperature intervals in a driving cycle is counted, the predicted life at each temperature is calculated by using the life model corrected by Arrhenius, and then the damage of a driving cycle is calculated ; ； ； In the formula For temperature Predicted lifespan Reference temperature Rated life under the following conditions For the first Actual operating temperature in each temperature range For the first The cumulative working time for each temperature range.

6. The method of life assessment of a DC bus capacitor of claim 1, wherein, Using the Monte Carlo method, the manufacturing tolerance of the capacitor is simulated by random sampling, a large number of samples are generated and life calculation is performed, and finally the reliability index of the capacitor is obtained by fitting the life data with Weibull distribution, specifically including: Assuming initial equivalent series resistance Subject to normal distribution to generate a predetermined number of initial equivalent series resistance Random sample; For each sample , steps S1 to S3 are performed, calculating a corresponding lifetime value , a lifetime distribution dataset is formed; The data set is fitted with a two-parameter Weibull distribution, whose cumulative distribution function is: ; where, is the reliability function, is the natural base, is time, is the scale parameter, is the shape parameter; extracting a key reliability index; wherein the reliability index comprises a B10 lifetime, i.e., a time at which 90% of capacitor samples are still able to work normally; ; wherein is a B10 lifetime; Capacitor bank reliability evaluation; the life of the capacitor bank is calculated by Weibull distribution function; ； In the formula For the overall reliability of the capacitor bank, , … These are the 1st, 2nd... capacitors in the capacitor bank, respectively. The reliability of each capacitor.

7. A lifetime evaluation device for a DC bus capacitor, characterized by A life evaluation method for a DC bus capacitor according to any one of claims 1 to 6; The life evaluation device comprises: A current acquisition module for establishing a simulation model of the motor drive system based on the typical driving cycle of the target electric vehicle, and obtaining the ripple current time sequence of the DC bus capacitor in the entire driving cycle; a temperature acquisition module for converting the ripple current time series data into capacitor hotspot temperature time series by establishing a second-order RC thermal network model of the capacitor through finite element thermal simulation fitting; a damage accumulation module for calculating the cumulative damage of the capacitor under the hotspot temperature time series based on linear cumulative damage theory, and introducing an aging feedback mechanism in the damage accumulation process to update the equivalent series resistance value of the capacitor in real time; an index module for generating a large number of samples and performing life calculation by simulating capacitor manufacturing tolerances through random sampling using the Monte Carlo method, and finally fitting the life data using the Weibull distribution to obtain the reliability index of the capacitor.

8. A life assessment device for a DC bus capacitor, characterized by The computer readable storage medium comprises a computer program stored therein, wherein the computer program is executable by the processor to implement the life evaluation method of the DC bus capacitor according to any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that, The computer readable storage medium comprises a computer program stored therein, wherein the computer program is executable by the processor to implement the life evaluation method of the DC bus capacitor according to any one of claims 1 to 6.

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